{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:L4HBADMOISESJFEZM6ZEOTNP5K","short_pith_number":"pith:L4HBADMO","canonical_record":{"source":{"id":"2607.29175","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2026-07-31T08:52:26Z","cross_cats_sorted":[],"title_canon_sha256":"065fdee97e0ce39c2c0286f723f249d169bb167d41b4dc5a08fa0300ac81b34f","abstract_canon_sha256":"a52e7cbc7d105c113dc5b385d1150565b671bb8ce90ca6a3392ecaa5d3353aa8"},"schema_version":"1.0"},"canonical_sha256":"5f0e100d8e448924949967b2474dafeabaf2b19d3b5e834f82ed63c898be5093","source":{"kind":"arxiv","id":"2607.29175","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.29175","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"arxiv_version","alias_value":"2607.29175v1","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.29175","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"pith_short_12","alias_value":"L4HBADMOISES","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"pith_short_16","alias_value":"L4HBADMOISESJFEZ","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"pith_short_8","alias_value":"L4HBADMO","created_at":"2026-08-03T01:20:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:L4HBADMOISESJFEZM6ZEOTNP5K","target":"record","payload":{"canonical_record":{"source":{"id":"2607.29175","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2026-07-31T08:52:26Z","cross_cats_sorted":[],"title_canon_sha256":"065fdee97e0ce39c2c0286f723f249d169bb167d41b4dc5a08fa0300ac81b34f","abstract_canon_sha256":"a52e7cbc7d105c113dc5b385d1150565b671bb8ce90ca6a3392ecaa5d3353aa8"},"schema_version":"1.0"},"canonical_sha256":"5f0e100d8e448924949967b2474dafeabaf2b19d3b5e834f82ed63c898be5093","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-03T01:20:29.085933Z","signature_b64":"9ElULD9foQ896/f3WxFSLO+8NebrXC7SUpvrDhwzHJyxsOORjxY6oygJbr9qUNqMIQGnljhQCIl1hLrmf1ZxCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5f0e100d8e448924949967b2474dafeabaf2b19d3b5e834f82ed63c898be5093","last_reissued_at":"2026-08-03T01:20:29.084406Z","signature_status":"signed_v1","first_computed_at":"2026-08-03T01:20:29.084406Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.29175","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-03T01:20:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BADTAAzZeKqXWpgr02iKmOBLy1RQvmacblnbqbANH1XAzYiNZWCW2DN0t3aDmpS1rFh96jN5PzZ4+xf3FxXGBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T10:51:20.597927Z"},"content_sha256":"87aa5303a19c4b54f1759fd847332f220c9c5be36c3a508fc7526ebedf63f87c","schema_version":"1.0","event_id":"sha256:87aa5303a19c4b54f1759fd847332f220c9c5be36c3a508fc7526ebedf63f87c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:L4HBADMOISESJFEZM6ZEOTNP5K","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Execution-First Synthetic Tool-Use Trace Generation for LLM Agents","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Adam Elwood, Alaa Boukhary, Francesco Giannuzzo, Gerard Conangla, Hafsa Ouajdi, Paolo Papotti","submitted_at":"2026-07-31T08:52:26Z","abstract_excerpt":"Agentic software-engineering and industrial systems increasingly operate through executable workflows rather than code genera- tion alone: they search artifacts, invoke tools, inspect structured observations, and query databases. Training these agents requires supervision data that captures valid tool interactions and executable workflows. However, traditional query-first data synthesis can fail because plausible user requests may not correspond to valid tool sequences, compatible parameters, or available data. To address this limitation, we propose SyntheticAgentTraceQA, an execution- first f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.29175","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.29175/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-03T01:20:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Xs7id+yofLRFo4cHw5kUfq1T3a2EI++mokULfmGrAA7rIww+ojWrYWP0beuSy9q64GHGoUdX9uGXez+6i2IeCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T10:51:20.598432Z"},"content_sha256":"23b9b4cbf78d680171dfe9bbf47748967e83907c32cba453fdf0b356e54ef9de","schema_version":"1.0","event_id":"sha256:23b9b4cbf78d680171dfe9bbf47748967e83907c32cba453fdf0b356e54ef9de"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:L4HBADMOISESJFEZM6ZEOTNP5K","target":"integrity","payload":{"note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.1038/s42256-024-00832-8) was visible in the surrounding text but could not be confirmed against doi.org as printed.","snippet":"Andres M. Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D. White, and Philippe Schwaller. 2024. Augmenting Large Language Models with Chemistry Tools.Nature Machine Intelligence6 (2024), 525–535. doi:10.1038/s42256-024- 00832-8","arxiv_id":"2607.29175","detector":"doi_compliance","evidence":{"ref_index":3,"verdict_class":"incontrovertible","resolved_title":null,"printed_excerpt":"10.1038/s42256-024-","reconstructed_doi":"10.1038/s42256-024-00832-8"},"severity":"advisory","ref_index":3,"audited_at":"2026-08-03T12:18:25.527849Z","event_type":"pith.integrity.v1","detected_doi":"10.1038/s42256-024-00832-8","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"recoverable_identifier","evidence_hash":"2958343549d43510bfbd811012ae5215827d23d470d5243cbb4926b6b7501eed","paper_version":1,"verdict_class":"incontrovertible","resolved_title":null,"detector_version":"1.1.0","detected_arxiv_id":null,"integrity_event_id":17627,"payload_sha256":"bec52a8b4810abb7df1a75402ed30b032144b824329703e6d3a2e278489480ff","signature_b64":"sHMDGfmFBvsYtvuI4nkjdBtM2fLvQ06wfFloaK7WXTOoFNagv1XByheW8a/cBq+8elkbVyjPsWAq96UWsQxdDQ==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-03T12:18:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rEPbVZ8BJ/pn0TF/doxeV7xpXQYmHCmJ8fENgZEr+Rp9R0SReQh/1/1kVgOjsD4dgjpayQjW8wrGPuv6A3axBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T10:51:20.602154Z"},"content_sha256":"52fcecdc8fff4acb1f510b5c5d439219be0f84876a2210279666ca13b2bf574c","schema_version":"1.0","event_id":"sha256:52fcecdc8fff4acb1f510b5c5d439219be0f84876a2210279666ca13b2bf574c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/L4HBADMOISESJFEZM6ZEOTNP5K/bundle.json","state_url":"https://pith.science/pith/L4HBADMOISESJFEZM6ZEOTNP5K/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/L4HBADMOISESJFEZM6ZEOTNP5K/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-04T10:51:20Z","links":{"resolver":"https://pith.science/pith/L4HBADMOISESJFEZM6ZEOTNP5K","bundle":"https://pith.science/pith/L4HBADMOISESJFEZM6ZEOTNP5K/bundle.json","state":"https://pith.science/pith/L4HBADMOISESJFEZM6ZEOTNP5K/state.json","well_known_bundle":"https://pith.science/.well-known/pith/L4HBADMOISESJFEZM6ZEOTNP5K/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:L4HBADMOISESJFEZM6ZEOTNP5K","merge_version":"pith-open-graph-merge-v1","event_count":3,"valid_event_count":3,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"a52e7cbc7d105c113dc5b385d1150565b671bb8ce90ca6a3392ecaa5d3353aa8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2026-07-31T08:52:26Z","title_canon_sha256":"065fdee97e0ce39c2c0286f723f249d169bb167d41b4dc5a08fa0300ac81b34f"},"schema_version":"1.0","source":{"id":"2607.29175","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.29175","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"arxiv_version","alias_value":"2607.29175v1","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.29175","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"pith_short_12","alias_value":"L4HBADMOISES","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"pith_short_16","alias_value":"L4HBADMOISESJFEZ","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"pith_short_8","alias_value":"L4HBADMO","created_at":"2026-08-03T01:20:29Z"}],"graph_snapshots":[{"event_id":"sha256:23b9b4cbf78d680171dfe9bbf47748967e83907c32cba453fdf0b356e54ef9de","target":"graph","created_at":"2026-08-03T01:20:29Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2607.29175/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Agentic software-engineering and industrial systems increasingly operate through executable workflows rather than code genera- tion alone: they search artifacts, invoke tools, inspect structured observations, and query databases. Training these agents requires supervision data that captures valid tool interactions and executable workflows. However, traditional query-first data synthesis can fail because plausible user requests may not correspond to valid tool sequences, compatible parameters, or available data. To address this limitation, we propose SyntheticAgentTraceQA, an execution- first f","authors_text":"Adam Elwood, Alaa Boukhary, Francesco Giannuzzo, Gerard Conangla, Hafsa Ouajdi, Paolo Papotti","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2026-07-31T08:52:26Z","title":"Execution-First Synthetic Tool-Use Trace Generation for LLM Agents"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.29175","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:87aa5303a19c4b54f1759fd847332f220c9c5be36c3a508fc7526ebedf63f87c","target":"record","created_at":"2026-08-03T01:20:29Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"a52e7cbc7d105c113dc5b385d1150565b671bb8ce90ca6a3392ecaa5d3353aa8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2026-07-31T08:52:26Z","title_canon_sha256":"065fdee97e0ce39c2c0286f723f249d169bb167d41b4dc5a08fa0300ac81b34f"},"schema_version":"1.0","source":{"id":"2607.29175","kind":"arxiv","version":1}},"canonical_sha256":"5f0e100d8e448924949967b2474dafeabaf2b19d3b5e834f82ed63c898be5093","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5f0e100d8e448924949967b2474dafeabaf2b19d3b5e834f82ed63c898be5093","first_computed_at":"2026-08-03T01:20:29.084406Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-03T01:20:29.084406Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9ElULD9foQ896/f3WxFSLO+8NebrXC7SUpvrDhwzHJyxsOORjxY6oygJbr9qUNqMIQGnljhQCIl1hLrmf1ZxCQ==","signature_status":"signed_v1","signed_at":"2026-08-03T01:20:29.085933Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.29175","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:87aa5303a19c4b54f1759fd847332f220c9c5be36c3a508fc7526ebedf63f87c","sha256:23b9b4cbf78d680171dfe9bbf47748967e83907c32cba453fdf0b356e54ef9de","sha256:52fcecdc8fff4acb1f510b5c5d439219be0f84876a2210279666ca13b2bf574c"],"state_sha256":"0daaf217ebf0434e0c88839ab25e87be7d0c652285550f6b97d5e799f7e2a74b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Qz1WBGP7BtmZo+pPOx2s0DWt/uvW+eCymCFcJfzwOu7fWSl2FdqPX70riTjjufg2XT0vpw2/QvTnu75vJdC8Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T10:51:20.604419Z","bundle_sha256":"36c934c172b27952aa718ee207315e56ecf98326d0fe91db876ae841528cd7ef"}}